Systemic therapy for advanced carcinoid tumors: where do we go from here?

Riferimento: 
J Natl Compr Canc Netw. 2012 Jun 1;10(6):785-93.
Autori: 
Paulson AS, Bergsland EK.
Fonte: 
J Natl Compr Canc Netw. 2012 Jun 1;10(6):785-93.
Anno: 
2012
Azione: 
Gli analoghi della somatostatina (SSTa) sono abitualmente utilizzati per controllare i sintomi ormone-mediati (sindrome carcinoide) dei tumori carcinoidi.
Target: 
Analoghi della somatostatina/tumori carcinoidi.

ABSTRACT
 

Carcinoid tumors are relatively indolent, but the treatment of advanced disease remains a challenge. Liver-directed therapies are a consideration in patients with liver-dominant disease. Somatostatin analogs (SSTa) are routinely used to control hormone-mediated symptoms (carcinoid syndrome), but the identification of systemic agents with antitumor efficacy has proven difficult. Aside from octreotide for small bowel carcinoid (which is associated with delayed progression), no treatment has proven antitumor activity. Chemotherapy seems to be of limited value. The role of interferon is also controversial; it is typically used after failure of octreotide. Peptide receptor radionuclide therapy may have activity in patients with SST receptor-expressing tumors, but randomized controlled trials are lacking. Advances in the understanding of the mechanisms underlying tumor progression have led to the identification of several potential therapeutic targets (including the vascular endothelial growth factor [VEGF] and mammalian target of rapamycin [mTOR] signaling pathways), but none has been definitively validated in carcinoid. Everolimus is associated with a trend toward improved progression-free survival in patients with progressive carcinoid, but is not approved for this indication. Therefore, a serious unmet need remains for additional therapeutic strategies for patients with advanced disease. Several avenues are under study, including the use of novel SSTa; VEGF and mTOR inhibitors; and agents that interfere with insulin growth factor 1 receptor and AKT signaling. Moving forward, optimizing patient selection based on clinical features or biomarkers holds promise for identifying individuals most likely to benefit from therapy.